Effective Management/leadership of Data Processing Projects PDF Download

Author: Raymond P. Wenig
Publisher:
ISBN:
Category : Electronic data processing
Languages : en
Pages : 265

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Book Description

Author: Harjit Singh
Publisher: FT Press
ISBN: 0134190491
Category : Business & Economics
Languages : en
Pages : 412

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Book Description
To manage projects, you must not only control schedules and costs: you must also manage growing operational uncertainty. Today’s powerful analytics tools and methods can help you do all of this far more successfully. In Project Management Analytics, Harjit Singh shows how to bring greater evidence-based clarity and rationality to all your key decisions throughout the full project lifecycle. Singh identifies the components and characteristics of a good project decision and shows how to improve decisions by using predictive, prescriptive, statistical, and other methods. You’ll learn how to mitigate risks by identifying meaningful historical patterns and trends; optimize allocation and use of scarce resources within project constraints; automate data-driven decision-making processes based on huge data sets; and effectively handle multiple interrelated decision criteria. Singh also helps you integrate analytics into the project management methods you already use, combining today’s best analytical techniques with proven approaches such as PMI PMBOK® and Lean Six Sigma. Project managers can no longer rely on vague impressions or seat-of-the-pants intuition. Fortunately, you don’t have to. With Project Management Analytics, you can use facts, evidence, and knowledge—and get far better results. Achieve efficient, reliable, consistent, and fact-based project decision-making Systematically bring data and objective analysis to key project decisions Avoid “garbage in, garbage out” Properly collect, store, analyze, and interpret your project-related data Optimize multi-criteria decisions in large group environments Use the Analytic Hierarchy Process (AHP) to improve complex real-world decisions Streamline projects the way you streamline other business processes Leverage data-driven Lean Six Sigma to manage projects more effectively

Author: Raymond P. Wenig
Publisher:
ISBN:
Category : Electronic data processing
Languages : en
Pages : 290

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Book Description

Author: Kirill Dubovikov
Publisher: Packt Publishing Ltd
ISBN: 1838824561
Category : Computers
Languages : en
Pages : 276

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Book Description
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learnUnderstand the underlying problems of building a strong data science pipelineExplore the different tools for building and deploying data science solutionsHire, grow, and sustain a data science teamManage data science projects through all stages, from prototype to productionLearn how to use ModelOps to improve your data science pipelinesGet up to speed with the model testing techniques used in both development and production stagesWho this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.

Author: Seweryn Spalek
Publisher: CRC Press
ISBN: 0429786360
Category : Business & Economics
Languages : en
Pages : 222

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Book Description
This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book’s integrated approach to investigating both fields enhances the value of research findings.

Author:
Publisher:
ISBN:
Category : Industrial engineering
Languages : en
Pages : 122

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Book Description

Author: Robert K. Wysocki
Publisher: Wiley + ORM
ISBN: 0470446536
Category : Computers
Languages : en
Pages : 547

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Book Description
Why another book on software project management? For some time, the fields of project management, computer science, and software development have been growing rapidly and concurrently. Effective support for the enterprise demands the merging of these efforts into a coordinated discipline, one that incorporates best practices from both systems development and project management life cycles. Robert K. Wysocki creates that discipline in this book--a ready reference for professionals and consultants as well as a textbook for students of computer information systems and project management. By their very nature, software projects defy a "one size fits all" approach. In these pages you will learn to apply best-practice principles while maintaining the flexibility that's essential for successful software development. Learn how to make the planning process fit the need * Understand how and why software development must be planned on a certainty-to-uncertainty continuum * Categorize your projects on a four-quadrant model * Learn when to use each of the five SDPM strategies--Linear, Incremental, Iterative, Adaptive, and Extreme * Explore the benefits of each strategic model and what types of projects it supports best * Recognize the activities that go into the Scoping, Planning, Launching, Monitoring/Controlling, and Closing phases of each strategy * Apply this knowledge to the specific projects you manage * Get a clear picture of where you are and how to get where you want to go

Author: Kristoffer Bjärkefur
Publisher: World Bank Publications
ISBN: 1464816956
Category : Business & Economics
Languages : en
Pages : 388

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Book Description
Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University

Author: James W. Cortada
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 232

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Book Description

Author: Hamish Donaldson
Publisher: New York : Wiley, c1978, 1979 printing.
ISBN:
Category : Business & Economics
Languages : en
Pages : 288

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Book Description